ABSTRACT
Water footprint (WF), a comprehensive indicator of water resources appropriation, has evolved as an efficient tool to improve the management and sustainability of water resources. This study quantifies the blue and green WF of major cereals crops in India using high resolution soil and climatic datasets. A comprehensive modelling framework, consisting of Evapotranspiration based Irrigation Requirement (ETIR) tool, was developed for WF assessment. For assessing climate change impact on WF, multi-model ensemble climate change scenarios were generated using the hybrid-delta ensemble method for RCP4.5 and RCP6.0 and future period of 2030s and 2050s. The total WF of the cereal crops are projected to change in the range of - 3.2 to 6.3% under different RCPs in future periods. Although, the national level green and blue WF is projected to change marginally, distinct trends were observed for Kharif (rainy season-June to September) and rabi (winter season-October to February) crops. The blue WF of paddy is likely to decrease by 9.6%, while for wheat it may increase by 4.4% under RCP4.5 during 2050s. The green WF of rabi crops viz. wheat and maize is likely to increase in the range of 20.0 to 24.1% and 9.9 to 16.2%, respectively. This study provides insights into the influences of climate change on future water footprints of crop production and puts forth regional strategies for future water resource management. In view of future variability in the WFs, a water footprint-based optimization for relocation of crop cultivation areas with the aim of minimising the blue water use would be possible management alternative.
ABSTRACT
Fruit flies are the most serious economic insect pests of mango in India and other parts of the world. Under future climate change, shifts in temperature will be a key driver of ecosystem function especially in terms of insect pest dynamics. In this study, we predicted the voltinism of the three economically important fruit fly species viz., Bactrocera dorsalis (Hendel), Bactrocera correcta (Bezzi) and Bactrocera zonata (Saunders) of mango from 10 geographical locations in India using well established degree day approaches. Daily minimum and maximum temperature data were generated by using seven General Circulation Models (GCMs) along with their ensemble, in conjunction with the four representative concentration pathways (RCPs) scenarios (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5) and three time periods (2020, 2050 and 2080) generated from MarkSim® DSSAT weather file generator. Historical data from 1969-2005 of these 10 locations were considered as baseline period. Under future predicted climates, model outputs indicates that all three fruit fly species will produce higher number of generations (1-2 additional generations) with 15-24% reduced generation time over the baseline period. The increased voltinism of fruit fly species due to increased temperature may lead to ≃5% higher infestation of mango fruits in India by the year 2050. Analysis of variance revealed that 'geographical locations' explained 77% of the total variation in voltinism followed by 'time periods' (11%). Such increase in the voltinism of fruit flies and the consequent increases in the infestation of mango fruits are likely to have significant negative impacts on mango protection and production.
